Abstract
This research concludes an overall summary of the publications so far on the applied Machine Learning (ML) techniques in different phases of Software Development Life Cycle (SDLC) that includes Requirement Analysis, Design, Implementation, Testing, and Maintenance. We have performed a systematic review of the research studies published from 2015-2021 and revealed that Software Requirements Analysis phase has the least number of papers published; in contrast, Software Testing is the phase with the greatest number of papers published.
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Navaei, M., & Tabrizi, N. (2022). Machine Learning in Software Development Life Cycle: A Comprehensive Review. In International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE - Proceedings (pp. 344–354). Science and Technology Publications, Lda. https://doi.org/10.5220/0011040600003176
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